Definitions
Artificial Intelligence (AI)
Technologies such as computer systems and software that are capable of simulating human cognition and performing complex tasks such as learning, problem solving, and decision making.1
Generative Artificial Intelligence (GenAI)
Generative Artificial Intelligence is a type of artificial intelligence that not only learns information and performs tasks, but can also use the data it is trained on to create new content such as text, images, audio, and video.2
Other Key Terms
Algorithms - a set of instructions designed tell a computer how to complete a task.3
Chatbot - a computer program that can "converse" with a human user through text or voice and understands one or more natural languages (i.e. English).4
Deep Learning - a type of machine learning that uses neural networks to process information similar to the way a human brain does.5
Large Language Models (LLMs) - a type of deep learning algorithm that uses neural networks to learn by tracking relationships in sequential data.6
Machine Learning - a subsection of artificial intelligence that focuses on enabling computers to use experiences to learn new behavior, rather than being explicitly programmed.5
Artificial Neural Networks (ANN) - a machine learning algorithm modeled after the biological neural networks of the brain.7
Prompt Engineering - the process of refining what you want an AI program to do.8
References
1. Stryker, C., & Kavlakoglu, E. (2024). What is artificial intelligence (AI)? IBM. https://www.ibm.com/think/topics/artificial-intelligence
2. Zewe, A. (2023). Explained: Generative AI. MIT News. https://news.mit.edu/2023/explained-generative-ai-1109
3. National Library of Medicine. (2022). Algorithm. The NNLM Data Glossary. https://www.nnlm.gov/guides/data-glossary/algorithm
4. Adamopoulou, E., & Moussiades, L. (2020). An overview of chatbot technology. In I. Maglogiannis, L. Iliadis, & E. Pimenidis (Eds.), Artificial intelligence applications and innovations: 16th IFIP WG 12.5 international conference, AIAI 2020, Neos Marmaras, Greece, June 5–7, 2020, Proceedings, Part II (pp. 373–383). https://doi.org/10.1007/978-3-030-49186-4_31
5. Coursera. (2025). Deep learning vs. machine learning: A beginner’s guide. https://www.coursera.org/articles/ai-vs-deep-learning-vs-machine-learning-beginners-guide
6. NVIDIA. (2025). Large language models explained. https://www.nvidia.com/en-us/glossary/large-language-models/
7. Choi, R. Y., Coyner, A. S., Kalpathy-Cramer, J., Chiang, M.F., & Campbell, J. P. (2020). Introduction to machine learning, neural networks, and deep learning. Translational Vision Science & Technology, 9(2). https://doi.org/10.1167/tvst.9.2.14.
8. Coursera. (2024). What is prompt engineering? Definition and examples. https://www.coursera.org/articles/what-is-prompt-engineering
Looking for more information?
If you have an NSU SharkCard or an Alvin Sherman Library Card, you can check out some of these additional articles about Artificial Intelligence from our NSU databases.
- Artificial intelligence. (2024). Gale Opposing Viewpoints Online Collection.
- Campbell, J. (2023). Generative artificial intelligence. Salem Press Encyclopedia of Science.
- Doermann, D. S. (2025). Artificial intelligence. World Book Advanced.
- Tantawi, R. (2024). Machine learning. Salem Press Encyclopedia.
- Whitson, G. M. (2024). Artificial intelligence. Salem Press Encyclopedia of Science.
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